Despite the vast majority (85 to 90%) of the human genetic diversity being observed within any human population, 10 to 15% of the genetic variation emerges when comparing all human populations. This between-population genetic variation is reflected in the amount of genetic similarity among humans, usually referred to as genomic or genetic ancestry, and the ancestry profile pattern can be even more complex when the populations are admixed, containing contributions from different ancestral origins. The genetic ancestry can be estimated using genomic data by methods that summarize the genetic diversity among individuals.
There are currently two major approaches underlying ancestry inferences: i) global ancestry, which is the estimate of the individual ancestry proportions (i.e., African and European ancestry) across the genome; and ii) local ancestry, which is based on the idea that an admixed individual's genome is a mosaic of fragments from different ancestral origins, and aims to infer the ancestry of each chromosome position. Remarkably, global ancestry is known to be associated with different biological traits, including rare and common diseases such as sickle cell disease and hypertension, which are overrepresented among those with African ancestry. Furthermore, local ancestry is being revealed as an important tool to identify loci associated with diseases through admixture mapping in populations such as Latinos and African Americans. Despite these recent advances, there is some controversy regarding genomic ancestry and some biological traits, such as skin color. Additionally, the literature warrants further studies about this topic, considering that some traits have never been studied in a genomic/local ancestry context.
This Research Topic aims to consider correlations between genomic ancestry (inferred by genomic data or by AIMs - ancestry informative markers) and any biological traits. We welcome the following article types: Original Research, Brief Research Report, Methods, Perspective, Review, Mini Review, and Systematic Review.
Image Credit: Victor Borda
Despite the vast majority (85 to 90%) of the human genetic diversity being observed within any human population, 10 to 15% of the genetic variation emerges when comparing all human populations. This between-population genetic variation is reflected in the amount of genetic similarity among humans, usually referred to as genomic or genetic ancestry, and the ancestry profile pattern can be even more complex when the populations are admixed, containing contributions from different ancestral origins. The genetic ancestry can be estimated using genomic data by methods that summarize the genetic diversity among individuals.
There are currently two major approaches underlying ancestry inferences: i) global ancestry, which is the estimate of the individual ancestry proportions (i.e., African and European ancestry) across the genome; and ii) local ancestry, which is based on the idea that an admixed individual's genome is a mosaic of fragments from different ancestral origins, and aims to infer the ancestry of each chromosome position. Remarkably, global ancestry is known to be associated with different biological traits, including rare and common diseases such as sickle cell disease and hypertension, which are overrepresented among those with African ancestry. Furthermore, local ancestry is being revealed as an important tool to identify loci associated with diseases through admixture mapping in populations such as Latinos and African Americans. Despite these recent advances, there is some controversy regarding genomic ancestry and some biological traits, such as skin color. Additionally, the literature warrants further studies about this topic, considering that some traits have never been studied in a genomic/local ancestry context.
This Research Topic aims to consider correlations between genomic ancestry (inferred by genomic data or by AIMs - ancestry informative markers) and any biological traits. We welcome the following article types: Original Research, Brief Research Report, Methods, Perspective, Review, Mini Review, and Systematic Review.
Image Credit: Victor Borda
